ABSTRACT The three PROJECTS in this Program will integrate transcriptional networks with cellular, molecular, electrophysiological, and physiological mechanisms that underlie dysphagia in mouse models of 22q11 Deletion Syndrome (22q11DS). CORE C, the Genomics and Bioinformatics Core, will generate high-quality cDNA libraries and RNA-Seq reads from RNA isolated from specific brain regions and nuclei, known to be important for feeding and swallowing, using specimens isolated from mouse genetic models of 22q11DS. The resulting RNA-Seq pair-end reads will be processed by our bioinformatics pipeline to generate the following genomics resources: i) assembly of reads into transcripts and alternatively spliced transcripts; ii) assembly of non-coding RNAs; iii) differential expression analysis; and iv) gene network and pathway over-representation analysis. These genomics resources serve two major roles. First, this information will serve to validate or invalidate hypotheses being tested in the Program PROJECTS. Second, we anticipate that our bioinformatics approach will generate new foundations, not envisioned or anticipated a priori at the Program's outset, for additional hypothesis testing at the molecular, physiological, and pharmacological (e.g., drug targeting of pathways to ameliorate disrupted feeding behavior) levels. Moreover, the genomics resources generated by CORE C will be deposited into a central repository (e.g., Sequence Read Archive of NCBI) for Data Sharing with other investigational groups, allowing them to mine our data and generate their own testable hypotheses. NARRATIVE CORE C will process and assess RNA-Seq transcriptome data for all 3 PROJECTS using an integrated computational pipeline. We will facilitate testing specific hypotheses defined in PROJECTS 1 and 2, as well as generate hypotheses that provide a framework for further analysis of molecular, cellular, and physiological mechanisms that underlie pediatric dysphagia (PROJECT 1), its developmental origin (PROJECT 2), or prevention (PROJECT 3). Our computational approach is anticipated to identify new diagnostic signatures or high priority pharmacologically accessible targets for intervention testing in animal models.